Using convolutional neural networks for predictive process analytics V Pasquadibisceglie, A Appice, G Castellano, D Malerba 2019 international conference on process mining (ICPM), 129-136, 2019 | 112 | 2019 |
A multi-view deep learning approach for predictive business process monitoring V Pasquadibisceglie, A Appice, G Castellano, D Malerba IEEE Transactions on Services Computing, 1-1, 2021 | 45 | 2021 |
Predictive process mining meets computer vision V Pasquadibisceglie, A Appice, G Castellano, D Malerba Business Process Management Forum: BPM Forum 2020, Seville, Spain, September …, 2020 | 41 | 2020 |
Contact-less real-time monitoring of cardiovascular risk using video imaging and fuzzy inference rules G Casalino, G Castellano, V Pasquadibisceglie, G Zaza Information 10 (1), 9, 2018 | 36 | 2018 |
ORANGE: outcome-oriented predictive process monitoring based on image encoding and CNNs V Pasquadibisceglie, A Appice, G Castellano, D Malerba, G Modugno IEEE Access 8, 184073-184086, 2020 | 25 | 2020 |
Fox: a neuro-fuzzy model for process outcome prediction and explanation V Pasquadibisceglie, G Castellano, A Appice, D Malerba 2021 3rd International Conference on Process Mining (ICPM), 112-119, 2021 | 24 | 2021 |
A fuzzy rule-based decision support system for cardiovascular risk assessment G Casalino, G Castellano, C Castiello, V Pasquadibisceglie, G Zaza Fuzzy Logic and Applications: 12th International Workshop, WILF 2018, Genoa …, 2019 | 21 | 2019 |
Fisdet: Fuzzy inference system development tool G Castellano, C Castiello, V Pasquadibisceglie, G Zaza International Journal of Computational Intelligence Systems 10 (1), 13-22, 2017 | 16 | 2017 |
A hierarchical fuzzy system for risk assessment of cardiovascular disease G Casalino, R Grassi, M Iannotta, V Pasquadibisceglie, G Zaza 2020 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS), 1-7, 2020 | 12 | 2020 |
PROMISE: Coupling Predictive Process Mining to Process Discovery V Pasquadibisceglie, A Appice, G Castellano, W van der Aalst Information Sciences, 2022 | 9 | 2022 |
A personal healthcare system for contact-less estimation of cardiovascular parameters V Pasquadibisceglie, G Zaza, G Castellano 2018 AEIT International Annual Conference, 1-6, 2018 | 7 | 2018 |
Darwin: An online deep learning approach to handle concept drifts in predictive process monitoring V Pasquadibisceglie, A Appice, G Castellano, D Malerba Engineering Applications of Artificial Intelligence 123, 106461, 2023 | 6 | 2023 |
STARDUST: a novel process mining approach to discover evolving models from trace streams V Pasquadibisceglie, A Appice, G Castellano, N Fiorentino, D Malerba IEEE Transactions on Services Computing, 2022 | 5 | 2022 |
A mobile app for contactless measurement of vital signs through remote Photoplethysmography G Casalino, G Castellano, A Nisio, V Pasquadibisceglie, G Zaza 2022 IEEE international conference on systems, man, and cybernetics (SMC …, 2022 | 4 | 2022 |
Leveraging Multi-view Deep Learning for Next Activity Prediction⋆ V Pasquadibisceglie, A Appice, G Castellano, D Malerba | 3 | 2021 |
Evaluating end-user perception towards a cardiac self-care monitoring process G Casalino, G Castellano, V Pasquadibisceglie, G Zaza Wireless Mobile Communication and Healthcare: 8th EAI International …, 2020 | 3 | 2020 |
JARVIS: Joining Adversarial Training With Vision Transformers in Next-Activity Prediction V Pasquadibisceglie, A Appice, G Castellano, D Malerba IEEE Transactions on Services Computing, 2023 | 2 | 2023 |
TSUNAMI-an explainable PPM approach for customer churn prediction in evolving retail data environments V Pasquadibisceglie, A Appice, G Ieva, D Malerba Journal of Intelligent Information Systems, 1-29, 2023 | | 2023 |
CENTAURO: An Explainable AI Approach for Customer Loyalty Prediction in Retail Sector G Andresini, A Appice, P Ardimento, AA Brunetta, AG Doronzo, G Ieva, ... International Conference of the Italian Association for Artificial …, 2023 | | 2023 |
Predictive Process Mining for Business Process Management Improvement V Pasquadibisceglie | | 2022 |